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This study investigates whether the recent extremely hot and dry summers (2003, 2015, 2018 and 2019) in Germany will be normal summer conditions under future climate change scenarios. Abnormally persistent high-pressure systems during these recent German summers maintained clear skies and dry conditions on the ground, resulting in record-breaking heat and drought conditions. Here, climate indices are calculated from the German Meteorological Service's (DWD) climate model reference-ensembles for periods 2031-2060 and 2071-2100 under greenhouse gas emission scenarios RCP 2.6 (11 ensemble members) and RCP 8.5 (21 ensemble members) and are compared with climate indices calculated from three DWD observational datasets (station data and gridded datasets: HYRAS and DWD Climate Monitoring Grids). The climate projections show increasing summer heat conditions for Germany throughout this century and a slight shift to dryer conditions, especially for the RCP 8.5 scenario. These recent extreme summers are often in the 15% hottest summers for RCP 2.6 in 2031-2060, 2071-2100 and the RCP 8.5 2031-2060 scenarios, but would be considered normal or even cool summers under the RCP 8.5 scenario in 2071-2100. Due to the combination of extreme heat and strong precipitation deficits, the climatic water balance and derived meteorological drought indicator values of these recent summers are often within the top 15% of projected extreme summer drought indices and are sometimes only matched by the most anomalous hot and dry summers in the DWD reference-ensembles, even for the high-emission RCP 8.5 scenario in 2071-2100. [ABSTRACT FROM AUTHOR]

The improvement of probabilistic assessments of extreme air temperature events is a major goal for agrometeorological studies. The regional frequency analysis based on L-moments (RFA-Lmom) has been successfully used to improve the study of hydrometeorological variables such as extreme rainfall events. This study investigated the hypothesis that the RFA-Lmom can be applied to extreme maximum (Tmax) and minimum (Tmin) air temperature data. The RFA-Lmon was calculated considering its original algorithm (multiplicative approach) and a new procedure referred as to additive approach. The suitability of both approaches was evaluated through Monte Carlo experiments, which simulated homogeneous and heterogeneous groups of Tmin and Tmax series, and through a case study based on weather stations situated in the state of São Paulo, Brazil. The results found in this study indicated that the RFA-Lmom can be applied to Tmax and Tmin data in tropical/subtropical regions such as the state of São Paulo. In addition, the additive approach consistently outperformed the multiplicative approach. Both discordance and heterogeneous measures presented their best performances when calculated under this new approach. The original goodness-of-fit measure may also be replaced by its bivariate extension when the group is formed by more than 15 series. [ABSTRACT FROM AUTHOR]

Extreme heat killed tens of thousands in Europe last summer–here's how this summer could be worse. [ABSTRACT FROM AUTHOR]